This invention relates to apparatus for validatina items of value, and to methods of calibrating such apparatus. The invention will be described in the context of coin validators, but is also applicable to banknote validators and validators for other items of value.
It is well known to take measurements of coins and apply acceptabilty tests to determine whether the coin is valid and the denomination of the coin. The acceptability tests are normally based on stored acceptability data. One common technique (see, e.g. GB-A-1 452 740) involves storing "windows", i.e. upper and lower limits for each test. If each of the measurements of a coin falls within a respective set of upper and lower limits, then the coin is deemed to be acceotable. The acceptability data could instead represent a predetermined value such as a median, the measurements then being tested to determine whether they lie within predetermined ranges of that value. Alternatively, the acceptance data could be used to modify each measurement and the test would then involve comparing the modified result with a fixed value or window. Alternatively, the acceptance data could be a look-up table which is addressed by the measurements, and the output of which indicates whether the measurements are suitable for a particular denomination (see, e.g. EP-A-0 480 736, and US-A-4 951 799). Instead of having separate acceptance criteria for each test, the measurements may be conbined and the result compared with stored acceptance data (cf. GB-A-2 238 152 and GB-A-2 254 949). Alternatively, some of these techniques could be combined, e.g. by using the acceptability data as coefficients (derived, e. g. using a neural network technique) for combining the measurements, and possibly for performing a test on the result. A still further possibility would be for the acceptability data to be used to define the conditions under which a test is performed (e.g. as in US-A-4 625 852).
It is known to use statistical techniques for deriving the data, e.g. by feeding many items into the validator and deriving the data from the test measurements in a calibration operation. It is also known for the validator to have an automatic recalibration function, sometimes known as "self-tuning", whereby the acceptance data is regularly updated on the basis of measurements performed during testing (see for example EP-A-0 155 126, GB-A-2 059 129, and US-A-4 951 799).
Normally, the acceptance data produced by the calibration operation is characteristic of the specific type of item to be validated. However, it is alternatively possible for the data to be independent of the properties of the item itself, and instead to be characteristic of just the validation apparatus (e.g. to represent how much the apparatus deviates in its measurements from a standard) so that this data in combination with further data representing the standard properties of an item are sufficient for validation.
It is sometimes desirable to calibrate or recalibrate an existing validator in the field (c.f. GB-A-2 199 978). For example, if the validator is arranged to validate a certain range of denominations, it may be desired to add a different denomination to that range, or to substitute one of those denominations for a different one. However, it is desirable to avoid the need to perform a very large number of tests during the calibration step if the apparatus is in the field, and also if the calibration is carried out using the internal control system of the validator or possibly using a hand-held terminal connected to the validator, there is a limit to the amount of available memory capacity, which inhibits the use of normal statistical techniques. The results therefore may be statistically unreliable.
EP-A-0 227 453 describes a coin validation apparatus which can be put into a "training" mode, in which a coin is inserted into the testing apparatus four times in succession, in order to develop acceptance criteria for validating further coins of the same type. Four sets of measurements are made to ensure that the results are representative of the particular coin type. The sets of measurements must match closely, in order for the operation to be completed. This prevents possible errors due to an incorrect coin being inserted. If four consecutive close matches are not found, then the entire operation must be repeated. Once there are four consecutive close matches, the measurements are then averaged, and the results define acceptance criteria used in the test mode of the apparatus. The use of only four measurements means that the resulting acceptance criteria may not be statistically very accurate. The disclosed technique requires the storage of all the measurements for all four coins, and therefore increasing the number of required tests during the calibration mode will substantially increase the memory requirements.